What shipped, when

Three new prompts this week: a point-by-point peer reviewer response letter that restates each comment and flags anything you have not actually fixed yet, a query letter for literary agents in the format agents expect, and a multi-pass self-editing checklist that separates structure, argument, and prose passes instead of one unfocused re-read.

New post: Why your AI's self-check misses its own mistakes, and the subagent recipe that catches them — research shows models miss identical errors in their own output far more often than in someone else's (a measured 64.5% blind-spot rate), and re-asking in the same thread does not fix it. The Claude Code subagent recipe that does: a fresh, independent, refutation-framed verifier with majority vote.

New post: Four AI labs spent $9 billion in eight weeks hiring the engineers you compete with — Anthropic, OpenAI, AWS, and Microsoft each launched a billion-dollar unit that embeds engineers inside enterprise customers between May 4 and July 2. Two are outside-funded joint ventures, two are internal cost centers, and the difference tells you what each is actually selling. What it means if you build or sell AI implementation work.

Added Vexp — a local dependency-graph context engine for AI coding agents (Claude Code, Cursor, and others) that cuts token spend by handing agents only the code that matters. All 10 existing picks re-checked and still live.

New post: ChatGPT Sites just left limited preview: what it replaces, and what it still cannot do — OpenAI opened its prompt-to-hosted-app builder to public beta July 9. The concrete test to run before dropping a Lovable, v0, or Bolt subscription, and the gaps (EEA/UK/Switzerland exclusion, no payment or health data, custom domain limits) to check first.

New post: Your Claude Code Explore subagent might be running on Opus without you asking — since v2.1.198, the built-in Explore subagent inherits your session model instead of defaulting to Haiku. The exact Explore.md override, the CLAUDE_CODE_SUBAGENT_MODEL env var, and the pricing math behind why it matters.

New post: GPT-5.6 is generally available: run the Terra migration test today — the government review gating Sol, Terra, and Luna to ~20 organizations lifted July 9. What actually changed, and the shadow-traffic test to run before moving production off GPT-5.5 Pro.

Added to the tools catalogue: Dify — open-source visual builder for production agentic workflows and RAG pipelines, 148,000+ GitHub stars; Firecrawl — open-source web scraping API that turns any site into clean data for LLM pipelines, 147,000+ stars; ComfyUI — node-based visual editor for diffusion model pipelines, used in production VFX and animation work, nearly 120,000 stars.

Added to the skill library: developer/implementation-plan-writer — turns a feature, refactor, or upgrade request into a phased, identifier-tagged implementation plan (REQ-, TASK-, RISK- style) that another agent or teammate can pick up without you standing by to explain it; web-ui/figma-design-implementer — reads a Figma file, frame, or component via MCP and implements it faithfully from the actual layout and style data, not a screenshot guess.

Added to the prompt library: mutual-action-plan-for-deal — a shared, dated timeline for a multi-stakeholder deal, built to send directly to the buying team; deal-qualification-gap-check — rates each MEDDIC-style qualification area as solid, assumed, or missing before a forecast call; retirement-plan-stress-test — fee-only fiduciary framing that surfaces assumptions, ranked risks, and what would invalidate the plan.

A practical walkthrough of ctx, a local CLI that indexes Claude Code, Cursor, Codex, and OpenCode session logs into searchable SQLite, verified end to end on a real multi-tool history (1,724 sessions, 241K events indexed in one pass). Covers install, search, and wiring it in as a skill or MCP server. Read it →

Search data showed the emergentintegrations.llm.chat guide ranking for queries that pair "emergentintegrations" with "python", while the page title never said Python. The title now names the Python package directly, and the page has been resubmitted for indexing.

The weekly trend read: Fable 5 leaves every Claude subscription on July 7 and becomes usage credits, Anthropic shipped spend alerts and model entitlements for Enterprise admins, employers are reportedly capping employee AI spend, and Meituan's MIT-licensed LongCat-2.0 gives high-volume teams an open-weights comparator. Includes a worked cost-per-run example. Read it →

Added Rafter (GitHub security scanning with AI-ready fixes), Reoon Email Verifier (bulk email validation), and Letterly (cross-app dictation) to the curated set. All 7 existing picks are still live and stayed in.

A skill defines what to check, a cloud routine defines when to run it, and git holds the memory between runs since routines clone the repo fresh every time. Covers the /schedule setup and the network-access default that lets a routine finish green while it silently fetched nothing. Read it →

Added to the tools catalogue: Skybridge — open-source TypeScript framework for building MCP Apps with rich UI that run inside Claude, ChatGPT, and VS Code from one codebase (1.9k GitHub stars); Hyper — knowledge layer that feeds a team's Docs, Slack, email, and GitHub into Claude Code, Cursor, and ChatGPT as shared context on every prompt.

Anthropic shipped Sonnet 5 on June 30 at $2/$10 per million tokens through August, close to Opus 4.8 quality. The new tokenizer counts up to 1.35x more tokens, so the rate card understates real spend. The post covers which work to move, how to set it up, and what to run before the September 1 price step. Read it →

Added to the prompt library: salary-negotiation-script — concrete scripts for offer counters and pushback responses; character-arc-development — wound-to-earned-change arc mapping with turning points; workflow-automation-strategy — ranks your manual workflows by feasibility and impact and names the first one to build.

/blog/structured-output-llm-json — Three structured output approaches that hold in production: OpenAI's response_format with strict: true, Anthropic's forced tool_choice pattern, and the Instructor library for cross-provider use with auto-retry. Covers the failure modes each approach leaves open — optional-field absence, type coercion edges, and schema complexity ceilings.

/learn/ai/ship-own-stack/emergentintegrations-llm-chat — Explains what the emergentintegrations Python package does, how to keep it running on your own infrastructure after leaving the Emergent platform, why there is no JavaScript SDK, and the exact code to replace it with direct OpenAI or Anthropic calls.

/blog/gpt-56-preview-pricing-regulatory-staging — Sol at $5/$30, Terra at $2.50/$15, Luna at $1/$6. GPT-5.6 launched June 26 in limited preview with access staged by White House request under EO 14409. The post covers what each tier is for, what the staging mechanism means for Q3 planning, and what to do with your current stack before general availability in early July.

A broad, hands-on guide to building your first AI agent: the three routes (no-code, a coding framework, or from scratch), a first build for each, the failure modes to design for, and curated resources. It opens with the question most people skip: whether you need an agent at all.

/deals — this week's curated set, AI picks first: ZeroRank AI (AI-search citation tracking, $69), Remalt (multi-LLM content canvas, $99), Rybbit (cookieless analytics, $49), Cleanlist AI (B2B lead enrichment, $79), TidyCal (booking + payments, $29), FlexiFunnels (AI-generated funnels, $49), and Sinosend (file delivery with data residency, $49). All confirmed live with meaningful runway.

A new pillar comparison of six AI app builders plus four head-to-heads — Lovable vs Replit, Lovable vs Emergent, Lovable vs Base44, and Lovable vs Cursor — comparing backend, stack, code ownership, lock-in, and pricing. We also refreshed 2026 pricing across the existing builder comparisons (Lovable's old $80 Pro tier and v0's $20 Premium plan are both retired).

Lovable gets a spotlight — a prompt-to-app builder that ships a real backend (Supabase auth + database) with one-click deploy, not just a front-end sandbox. The write-up covers where it fits (prototypes, internal tools, landing pages), where it doesn't, and how to plan your exit before the generated code becomes the thing you maintain.

/blog/openai-jalapeno-chip — OpenAI and Broadcom announced Jalapeño, a custom ASIC built for LLM inference. The post explains what ASICs are vs. GPUs, traces the Google TPU → Gemini pricing precedent, and gives builders a mental model for thinking about API cost trajectory over the next 12–24 months.

/prompts/design — three new design prompts:

• Creative Brief — structure a project brief before design starts: client, objective, target audience, key message, competitive context, tone, deliverables, and measurable success metrics on one page.
• Heuristic Evaluation — run Nielsen's 10 usability heuristics against any screen or flow: pass/partial/fail per heuristic, severity rating per violation, one-sentence fix, and a top-5 priority list ranked by severity × estimated fix effort.
• Micro-Interaction Design Spec — spec all 8 component states (default, hover, active, focus, loading, success, error, disabled) with CSS transition, duration, easing, and animated properties for engineering handoff.

/skills — two new developer skills:

• Doubt-Driven Development — CLAIM → EXTRACT → DOUBT → RECONCILE → STOP cycle for adversarial in-flight review of non-trivial design decisions. Runs before irreversible commits (data migrations, public API contracts, production deploys). Issues-only framing; zero findings is a valid outcome. Distinct from code review and AI-output verification — this targets the engineer's own pre-commitment decisions.
• Browser Testing with DevTools — verify a running UI via Chrome DevTools MCP: DOM assertions, console error checks, network call verification, Core Web Vitals recording, and screenshots at each step. Produces a structured test plan (navigate → assert → capture) readable in a PR diff. Requires Chrome DevTools MCP.

/tools — three additions:

• Wispr Flow (voice) — voice-to-text for every app on Mac, Windows, iOS, and Android; removes filler words and adapts tone per context.
• Steel (automation) — open-source browser API for AI agents with Playwright/Puppeteer compatibility, built-in proxies, and a self-hostable or managed cloud option.
• Baseten (llm) — production inference platform for deploying custom and open-source models with optimized runtimes for LLMs, TTS, transcription, and image generation.

Tool Drop — WriteVoice, a dictation tool that shapes your transcript for where it's going (Slack, Jira, Gmail, code comments), is $59 lifetime on AppSumo, down from $144. What it does, who it fits, and what to weigh before buying are in the spotlight. Affiliate link.

/skills — two new skills:

• Excalidraw Diagram Builder (diagram) — generates Excalidraw JSON where layout choices encode conceptual relationships: fan-outs for one-to-many, chains for sequences, overlapping boxes for shared ownership. Includes Playwright visual validation and brand-palette config. Distinct from Mermaid skills — targets whiteboard-style sharing with mixed audiences.
• OKR Design Facilitator (founder) — produces spec-checked quarterly OKRs using the Doerr/Measure What Matters framework: outcome vs. output KR test, independent measurability, defining completeness check, plus a weekly 0–10 confidence-scoring cadence with escalation triggers.

/tools — three additions:

• Viktor (automation) — AI agent that executes tasks end-to-end inside Slack and Microsoft Teams across 3,200+ tools.
• Octolane (sales-marketing) — AI-native CRM with agents for account research, follow-ups, and contact enrichment.
• MiniMax Hub (video) — desktop creative studio coordinating sub-agents across scripts, images, video, and audio.

/blog/build-a-20-case-eval-set-promptfoo — Green CI is not evidence the feature works. The 20 cases to write, the promptfoo YAML to run them, the four failure patterns to recognize (hallucination, drift, brittle-prompt, should-not-ship), and the pre-ship gate loop.

/skills — two new discovery-framework skills:

• Opportunity Solution Tree (founder) — build a structured OST from a North Star metric: outcome → opportunity nodes → solution branches → cheapest experiment. Includes Mermaid output and anti-patterns for common mis-uses (solutions disguised as opportunities, trees without experiments).
• Jobs to Be Done Analyzer (marketer) — JTBD job statements (when/I want to/so I can), three-dimensional job decomposition (functional/social/emotional), and four-forces switch analysis (push/pull/anxiety/attachment). Answers who you actually compete with in the customer's mind.

Added Architecture risk review (pressure-test a design before coding — 3 biggest risks + one alternative), Feynman learning loop (four-step explain → test → gap-fill → synthesize), and Voice-preserving editor (tighten a draft without losing your voice — every cut flagged with rationale).

Added Poolside (Laguna M.1 + XS.2 open-weight MoE models for agentic coding), API to MCP (convert any REST/GraphQL API into a hosted MCP server), and Atomic Mail Agentic (JMAP email inboxes for AI agents with MCP integration).

Claude Fable 5 is suspended — Nine days after a US government export control directive pulled Fable 5 and Mythos 5 from every user worldwide, the models remain offline. Covers what happened, which Claude models still work (Opus 4.8, Sonnet 4.6, Haiku 4.5), and how to swap model IDs if you're affected.

Each prompt in the /prompts library now has its own dedicated page (e.g. /prompts/productivity/sprint-retro-to-action-items) — a clean, linkable, copy-paste-ready URL for every single prompt, alongside the existing category pages. Each page has the full prompt, one-click copy, open-in-ChatGPT/Claude/Gemini, and related prompts in the same category. Better for sharing a specific prompt, and better for search.

Deepening the cluster that already pulls the most search traffic in /learn — moving off a no-code/AI builder onto a stack you own:

• Migrate from Bolt (bolt.new) — export to GitHub, deploy the Vite + React frontend to Netlify or Vercel, and add a real backend if it only had mock data.
• Migrate from v0 — v0 output is standard Next.js on the Vercel stack, so the work is owning the repo and swapping mock data for a real Supabase backend.

The migration hub now links six per-builder guides (Lovable, Replit, Emergent, Base44, Bolt, v0), and the existing four had their openings sharpened to lead with migration intent.

Eight new guides across /learn, answering the "how do I actually choose and run this stuff" questions:

New pillar — Choose the right AI (under Working with AI):

• Which AI model should you use? — by task, not benchmark; tiers; a default that survives the next release.
• Chat window or coding agent? — when to reach for which.
• Free vs paid AI — when the upgrade actually pays off.

New pillar — Running AI tools (under Stacks & systems):

• Installing CLI coding agents — Claude Code, Codex, Gemini CLI, Kimi; exact commands.
• What is MCP, and when do you need it?
• Setting up your first MCP server — hands-on with claude mcp add.

Decision hub (in Build with AI):

• Prompt, skill, RAG, knowledge base, or fine-tune? — cheapest-first decision order.
• RAG vs an indexed knowledge base — the distinction, and why most systems use both.

/learn/prompt-engineering/for-builders — the third Prompt Engineering pillar, for anyone embedding prompts in a product or workflow. Four guides, all published:

• Writing system prompts — persona, scope, guardrails, output format; system turn vs user turn, and iterating without regressing.
• Improving a prompt without guessing — the baseline → regression-test → targeted-change loop, and why even a 20-case eval set beats intuition.
• Prompt injection defense — how attacks override your system prompt, and the layered defenses that work: privilege separation, boundary tagging, output validation.
• Prompting across Claude, GPT, and Gemini — the practical differences and a process to port a prompt without rewriting it.

/skills — two new skills published today:

• Threat Model Builder (developer) — STRIDE threat modeling for features and API designs before implementation. Maps trust boundaries, attack surfaces, and produces a ranked mitigation table that feeds into ADRs or security review gates.
• Investor Outreach Sequencer (founder) — cold-start fundraising workflow: investor fit research, warm-intro mapping, and sequenced first-touch + follow-up email cadences. Distinct from investor-update-writer (which serves existing cap-table investors).

/prompts — three new entries across productivity, code, and analysis:

• Sprint retro → action items (productivity) — turns raw retro notes into grouped themes, root causes, and a table of action items with owners.
• Blameless post-mortem (code) — the shareable artifact after an incident: layered root cause, contributing factors, impact, and systemic action items.
• SWOT with strategic priorities (analysis) — full SWOT with impact ratings and "so what?" per point, derives top 3 strategic priorities and a quick win.

/tools — the catalog grows from 205 to 370 entries. One focused research pass per category, deduped against the existing library, each tool verified to be a real, live product. A slice of what's new:

• Coding / agentic dev: Antigravity, Amp, Jules, Kiro, CodeRabbit, Qodo, Trae
• LLM & inference: Groq, OpenRouter, Together AI, Fireworks AI, Cerebras
• Generative media: Higgsfield, Tavus, Topaz Labs, Photoroom, Speechify, Resemble AI
• Sales & marketing: FullEnrich, Cognism, Clearscope, Warmly — plus AI-SDR and enrichment tools
• Productivity & automation: Gumloop, Flowise, Langflow, Coda, ClickUp, Taskade
• Research: Undermind, Hebbia, STORM, Paperpal
• Local AI, evals & sandboxes: Open WebUI, vLLM, Promptfoo, Portkey, Northflank, Runloop

Browse the full set at /tools.

Blog — As of June 18, 2026, Gemini CLI and the Gemini Code Assist IDE extensions stop serving requests for Google AI Pro, Ultra, and free-tier users; Standard/Enterprise licenses and paid API keys are unaffected. The post breaks down exactly who's affected, what keeps working, and what Antigravity CLI carries over (Agent Skills, Hooks, Subagents, Extensions — without 1:1 parity).

Blog — SpaceX agreed to buy Cursor (Anysphere) for $60B in SpaceX stock, four days after the company's IPO. The post covers the deal terms, why SpaceX needed Cursor to replace the failed xAI, and what it means for builders using Cursor today.

Prompt library — Added 7 prompts across four categories: a structured research paper summary and cross-study comparison (research + analysis), a newsletter issue builder and landing page copy generator (writing), and two investor update templates — one for monthly updates, one for the "we missed the numbers" email (writing). All adapted from production prompt packs.

Best AI picks by role — Added 9 more "Best AI for X" surfaces: designers, HR teams, product managers, content creators, meeting notes, agencies, consultants, e-commerce operators, and researchers. Three fact-checked picks per role with explicit caveats on when each tool earns its cost.

Best AI picks by role — Added 7 new "Best AI for X" surfaces: sales reps, marketing managers, founders, engineers, customer support, cold email outreach, and image generation. Three opinionated picks per role, with specific reasoning on when each tool earns its cost.

Stop prompting. Start observing. — Before AI can replace any part of your week, you have to see it clearly. The one-week audit, the four-bucket sort, and the trap of automating work that shouldn't exist at all.

Title and meta descriptions on two /learn/ship-own-stack migration guides updated to better match search intent (position 4–7, 0% CTR → cleaner action-first copy).

Old prompt-craft URLs were indexed by Google but returning 404. Added 301 redirects to the new /learn/prompt-engineering/foundations paths.

Prompt Engineering is now a first-class category in /learn, alongside Working with AI, Building & Shipping, and Stacks & Systems.

Three pillars, twelve guides (four existing, four new, four coming soon):

Prompt fundamentals — the four foundations: what makes a prompt work, XML structure and roles, few-shot examples, and five patterns that work in any model.

Prompting techniques — four new guides: chain-of-thought prompting, prompt chaining, role prompting, structured output control.

Building with prompts — system prompts, iteration method, injection defense, cross-model porting — coming soon.

MCP in plain English — and what to install first — what the protocol is, what it isn't, the three primitives, and which three servers to install first.

Title and meta descriptions updated on three /learn/ship-own-stack pages to match GSC query intent.

How to write AGENTS.md so AI doesn't break your repo — seven sections in impact order, a Claude-draft workflow, and a 7-point checklist.

Workflows just got a new shape: outcome bundles — cross-role journeys priced at $12.49, sitting alongside the $19 role packs. Each is a spine plus five new deep workflows that get one outcome done end to end:

• Build, Ship & Host Your Own Product — idea → a hosted, paid product: auth + Stripe, CI/CD, monitoring, domain + email, cost control.
• Launch Your Product (GTM) — positioning, launch week, SEO foundation, measurement, and first customers, across the marketing, sales and founder packs.
• Ship an AI Feature on Claude — API integration, cost + quality tuning, RAG, observability, and pre-ship verification.

The bundles tie into three new free skills — hosting-stack-selector, auth-and-payments-setup, production-monitoring-setup. And workflow pages now show the skills and prompts each one references as clickable links, so the library is wired together instead of siloed.

Twenty-six new skills landed on /skills, bringing the library to 200. The biggest additions are on the developer side: a Claude API Builder (prompt caching + streaming by default), a Browser Automation Driver for end-to-end UI checks, React performance and composition reviewers, a Postgres performance reviewer, and test-driven-development. Marketers get a Voice-of-Customer researcher, a Marketing Psychology advisor, and SEO additions for site architecture and structured data. Each one is a self-contained SKILL.md you can install, written for utility rather than a tool dump — and de-duplicated against everything already in the library.

How to write AGENTS.md so AI doesn't break your repo — the standing instruction file every AI-built project needs and most skip. What to put in it (seven sections in order of impact), what the cost of skipping each section is, and a step-by-step workflow for having Claude draft one without ending up with 400 lines of generic filler. Closes with a 7-point checklist for the final file. Links out to /glossary/cursorrules and the working-with-existing-code guide.

Added a six-question FAQ section to How to migrate a Base44 app covering the questions that don't fit cleanly into the path walkthroughs: Builder plan gating, data export behavior, how to scope the SDK surface area before starting, hosting alternatives to Vercel, and whether the migration is reversible. The guide title also sharpened to surface "Vercel, eject, Supabase" — the three destination options — which is what search intent actually shows up as.

Filling a real gap in /learn/ai/ship-own-stack: how to migrate a project off the AI builder it was prototyped in. Each guide is written against the builder's own documentation, with the host-side migration paths covered end to end.

Four new guides:

• Migrate from Lovable — GitHub sync, Vite on Vercel, deciding whether to keep the Lovable-provisioned Supabase or move to your own, fixing auth redirect URLs, replacing Edge Functions.
• Migrate from Replit — following Railway's official Replit migration guide. Downloading the zip, removing .replit and replit.nix, translating the run command, migrating Postgres with pg_dump, replacing Replit Auth.
• Migrate from Emergent — splitting the FastAPI + React + MongoDB stack across Vercel (frontend), Railway/Render/Fly (backend) and MongoDB Atlas (data). mongodump/mongorestore, CORS, AI provider key rotation.
• Migrate from Base44 — three depths: move only the frontend (recommended starting point), eject to a new Base44 backend you own, or fully rebuild against Supabase + Postgres. Why partial migration is usually the right first move.

Hub guide rewritten: graduate-from-nocode is now broader than the original Lovable/Bolt scope, with the five graduation signals refined and explicit links into the per-builder pages. It also covers what graduating does not fix — speed, security, or operational time — which is the part most articles skip.

Why now: "migrate from X" queries for Lovable, Replit and Emergent have rising volume across SEO surfaces, none of the existing answers cover all four major builders with verified source citations, and the pillar already had the deploy-walkthrough that these guides hand off into.

/prompts — 65 new prompts across 10 categories (112 → 177 total):

• Code (+14): agent steering before edits, course-correct mid-task, incident investigation across logs and deploys, IaC plan translation, plain-English log queries, TDD with AI, codebase archaeology prompts
• Sales (+12): QBR talking points, strategic account plans, renewal pitch, battlecards, territory planning, exec pipeline updates
• Productivity (+10): quarterly OKRs with non-goals, hiring roadmaps, 1:1 templates, cross-team conflict mediation, exec briefings
• Analysis (+10): funnel drop-off with ranked hypotheses, customer health rubrics, A/B test interpretation, attrition detection, forecasts with confidence intervals
• Research (+9): competitor pricing benchmarks, regulatory landscape, compensation benchmarks, industry trends with evidence vs. narrative separated
• Writing (+8): PRD drafts with acceptance criteria, town hall talking points, reorg comms, vision statements
• Design (+2): customer journey maps, positioning matrices

/skills — 43 new skills across 8 packs (132 → 175 total):

• Developer (+11): CI/CD architect, MCP server builder, RAG architect, LLM cost + quality tuner, observability designer, SLO designer, dependency auditor, feature flags architect
• Founder (+11): CFO advisor, Chief AI Officer advisor, plan stress-tester, pre-mortem generator, adversarial board prep, first-customer interview loop
• Marketer (+10): cold email sequence, paid ads architect, A/B test coach, brand voice extractor, landing-page CRO audit, pricing page optimizer
• Sales-rep (+8): RFP responder, champion coaching plan, pricing conversation coach, multi-thread account
• Customer-success (+3): onboarding playbook builder, health score rubric designer, expansion play architect

End-of-May surface refresh covering the editorial layer on top of all the content shipped this week.

Three new spotlights on /spotlights:

• LLM Cost + Quality Tuner (skill) — the structured exercise for cutting LLM bills 30–70% without breaking outputs. Profiling first, then 7 ranked levers with quality risk per lever.
• OpusClip (tool-drop) — the long-video to short-clip pipeline that stopped being a hack. Active-speaker reframing that holds up, viral-score ranking that does the picking-work for you.
• May 2026 stack — understand before you build (monthly-stack) — the editorial thesis behind this month's shippings. Why we built Foundations + Paths + indie-tool-evaluation as a set, what we deliberately skipped (gamification, AppSumo dump, new pages), what is next.

/best — end-of-month review. All four surfaces (coding stack, research tools, free AI setup, prompts for writing) reviewed against the month's new releases and changes. Picks held in every case. Each surface has a new past[] entry documenting what was considered for inclusion and why the current ranking still wins.

Two complementary shippings to address the long tail of AI tools — both the mainstream gaps and the question of how to evaluate the indie tools that don't appear in mainstream listicles.

/tools — 8 additions filling category gaps:

• Productivity: Grammarly (writing assistant across every app), Sudowrite (AI for fiction and screenwriting), Superhuman (premium email with AI drafting)
• Video: OpusClip — long-form to short-clip pipeline with viral-score predictions
• Voice: PlayHT — 900+ voices across 140+ languages, multilingual TTS at scale
• Sales/Marketing: Vista Social (social media management), AdCreative.ai (AI-native ad creative with conversion predictions), Textio (hiring and performance language)

Brought /tools from 198 to 206 entries across the catalog.

New guide: Evaluating an indie AI tool before you commit — a 15-minute pre-commit checklist for any AI tool you're considering paying for. Covers wrapper-risk, team and funding signals, the changelog test, community signal, the "try your worst case" test, lock-in audit, and the LTD-specific risks (acquisition risk, feature gating, support cliff). Plus an honest read on when indie beats incumbent and when it doesn't.

Source: curated from ClickUp, Lindy, Lovable, and Alai's 2026 "best AI tools" lists; cross-checked against AINews's existing 198-tool catalog to find genuine gaps. AppSumo deals were considered but parked for a future /deals batch (documented in roadmap).

Two follow-ups to the /learn/paths feature.

Two new paths.

• Founder → AI-augmented operator — 9 guides, ~95 min. Foundation + customer-interview habit + architecture decisions + the solo-founder applied chapter.
• Designer → AI-assisted workflows — 7 guides, ~55 min. Prompt craft heavy (designers benefit disproportionately from few-shot), the designer playbook, and a bridge to building working prototypes.

Total: 5 paths now.

"You are on a path" indicator. When you open any guide that sits inside one or more paths, a small banner near the top tells you which path(s) the guide belongs to and the step position ("step 3 of 8"). One click takes you back to the path overview. Server-rendered, no JS cost.

Two related shippings in /learn — the technical-depth pillar and the multi-guide path feature that ties everything together.

New pillar: "How AI works" (foundations) — 8 substantial guides for the operator who wants to understand the mechanism, not just use it:

• How large language models work — the mental model that fixes most "why did AI do that" moments
• What is a token in AI? — the unit that controls cost and output
• Context windows explained — what they limit, what they do not, lost-in-the-middle effect
• Embeddings explained — how AI represents meaning as numbers
• Transformers and attention — the architecture under every modern model
• Fine-tuning vs RAG vs prompting — which one fits your problem
• How AI agents work (and where they break) — the mechanism + six predictable failure modes
• How to evaluate an LLM feature is working — without fooling yourself

New feature: Learning paths — three sequenced multi-guide routes through the library, shaped by role:

• Zero → AI-augmented operator — 8 guides, ~4 weeks at 15 min/week
• Engineer → AI-coding fluency — 9 guides, ~6 weeks at 15 min/week
• PM → AI-aware product thinking — 7 guides, ~3 weeks at 25 min/week

Source pattern: foundations distilled from Microsoft AI-For-Beginners and the broader academic curriculum; learning paths borrowed from DataCamp's role-based "how to learn AI" structure. Both adapted to AINews voice — utility-framed, model-agnostic, no buzzwords.

New guide in /learn/ai/get-started: Free AI courses worth your time (from the people who built it).

Opinionated short list — Anthropic Academy, OpenAI Academy, Google ML Crash Course + Analytics Academy, Hugging Face NLP Course, Elements of AI (University of Helsinki), Google Cloud Skills Boost.

For each: what it's good for, who it's for, and what to skip. With a suggested starting order by role at the end.

Also explicitly named what we left off and why (random YouTube playlists, "30 day boot camp" funnels, "100 prompts that change your life" lists). Filtering matters — the value isn't a longer list, it's a shorter one you can trust.

New pillar in /learn/ai: Prompt craft. The patterns that hold across every model — not "10 magic words" content, the actual fundamentals.

Three guides, model-agnostic, ship today:

• What makes a prompt actually work — the "brilliant but new employee" mental model, the colleague test, and the five patterns that move quality every time (specific format, why-not-just-what, examples, role assignment, constraints up front).
• Structuring prompts with XML, roles, and sections — when to start structuring (~200 words), why <tags> beat prose for long prompts, the role-1-sentence quality upgrade, and the hierarchy that matters at 20k+ tokens (instruction at the END).
• Few-shot examples: when they help, how to write them — the single highest-leverage technique. The 3 rules (relevant, diverse, structured), the 3–5 sweet spot, why one bad example corrupts the whole output, and the meta-trick of asking the model to critique your examples.

Source pattern: distilled from Anthropic's official prompt-engineering reference, generalized to be model-neutral. AINews voice — no "magic words," no "10x your AI productivity," utility over inspiration.

Eighteen substantial new skills added to the four highest-engagement role packs. Each one is a self-contained installable skill — methodology + workflow + anti-patterns + tone notes. Source material curated from the broader Claude Code agent-skills ecosystem (MIT-licensed), then rewritten for AINews voice (utility framing, no Claude-Code-specific commands, no enterprise-skill-tier theatrics).

By pack:

• /skills/founder (12 → 17): Plan Stress-Tester, Pre-Mortem Generator, Hard Call Framework, Adversarial Board Prep, First-Customer Interview Loop.
• /skills/sales-rep (15 → 20): RFP / Security-Questionnaire Responder, Deal-Desk Discount Justifier, Champion Coaching Plan, Multi-Thread the Account.
• /skills/developer (16 → 20): Codebase Onboarding Doc Builder, SLO + Error Budget Designer, LLM Cost + Quality Tuner, Dependency + CVE Auditor.
• /skills/marketer (13 → 17): Technical SEO Audit, Answer-Engine Optimization Brief, Landing-Page Conversion Audit, Referral Program Designer.

Brought /skills from 132 to 150 skills across 12 role packs.

Companion batch to today's code-prompt drop. 26 additions across six categories — strategic work that's usually buried in role-specific playbooks, generalized into AINews voice.

By category:

• /prompts/sales (10 → 16): strategic account plans, battlecards with "where they win" honesty, renewal pitches grounded in real outcome numbers, territory planning, exec pipeline updates, public-domain proof-point research.
• /prompts/productivity (11 → 16): quarterly OKRs with explicit non-goals, hiring roadmaps with the rationale baked in, 1:1 templates that surface what skip-levels miss, cross-team conflict mediation, exec briefings under 4 minutes.
• /prompts/writing (10 → 14): PRD drafts with observable acceptance criteria, town hall talking points, reorg comms sequenced by audience over 24–72h, vision statements that aren't corporate posters.
• /prompts/research (10 → 14): competitor pricing benchmarks (public-source only), regulatory landscape by region, compensation benchmarks with assumptions visible, 3-year industry trends with evidence vs. narrative separated.
• /prompts/design (10 → 12): customer journey maps with friction marked honestly, 2x2 positioning matrices that pressure-test self-flattering axes.
• /prompts/analysis (11 → 16): funnel drop-off with 3 ranked hypotheses, customer health rubrics that discriminate (not wallpaper), A/B test interpretation including confounders most readouts skip, attrition pattern detection, forecasts with confidence intervals.

Source pattern: generalized from OpenAI Academy's role-based prompt packs, rewritten to AINews multi-section voice — no "ChatGPT for X" framings, no "leverage / robust / seamless," utility over inspiration.

Fourteen additions to /prompts/code, targeting the gaps the existing 20 prompts didn't cover well: planning before agents touch code, steering them mid-task, and translating production signals into next moves.

Highlights:

• Plan a multi-file change before any edits — file list + risks + out-of-scope, before the agent writes a single line. Stops "rewrote half the project" outcomes.
• Course-correct without rewinding + Narrow a change that went too broad — the steering moves you need when the direction is right but the execution drifted.
• Investigate a production incident across logs, deploys, and config — ranked causes, each with the signal that confirms it. Not a single guess.
• Translate IaC plan output to plain English — Terraform / Pulumi / CDK plans → what's created, replaced, destroyed, what's dangerous. With an apply/don't-apply verdict.
• Query logs in plain English (and see the query) — ask, see the SQL/KQL, approve, run, interpret. With a scan-size guardrail.
• Drive implementation from tests (TDD with AI) — strict order: tests fail → approve → implement → green. Never weaken the test.
• Get oriented in a new codebase, Trace why code looks the way it does, Trace what happens when a user does X — the three onboarding / archaeology prompts you reach for in week one of a new repo.
• Map the edge cases the happy path is hiding — 8 categories of what-can-go-wrong with explicit "not covered" flagging.
• Plus: anchor to existing patterns, close coverage gaps without gaming the metric, diagnose from cloud-console screenshots.

Brought /prompts/code from 20 to 34 prompts.

Four new beginner-intent guides under /learn/ai/productivity-playbooks. Each one answers a specific work-intent query with a working model, concrete examples, and a clear "where it goes wrong" section — not generic tips:

• How to use AI for research — orient, find gaps, pressure-test, turn into output. With the verification step.
• How to write better emails with AI — 5-input model, revision-mode, ban-list, when not to use AI for email at all.
• How to use AI for meetings, notes, and follow-ups — decision extraction, action items with owners, same-hour follow-up.
• How to use AI for spreadsheets and analysis — formula generation, anomaly spotting, code-interpreter mode, and the math you can never trust AI to do alone.

Pillar renamed in nav from "Productivity playbooks" to "Use AI for work" — same URL, clearer entry point.

Several visual and SEO fixes shipped together:

• New favicon + logo matching the gradient-A brand. Header, footer, and all browser tabs share one identity now.
• Dark-mode contrast bug in all /learn guide pages fixed (prose prose-invert was always-inverted with conflicting overrides — body text was unreadable on dark backgrounds).
• Aurora background now edge-to-edge in both light and dark mode (the local hero gradient was being clipped inside the max-w-7xl container).
• 404 cleanup: /favicon.svg + /apple-touch-icon variants now resolve, eliminating ~830 404s/week (12% of all 404 traffic).
• Glossary page titles retargeted from "X — what it means in plain English" to "What is X?" for cleaner query match.
• Redirect for /imgs/logox.png (external link rot) → current brand icon.

Two-part RAG update driven by SEO data showing rising impressions on "rag", "rag meaning llm", "what is rag" queries hitting the glossary page.

• /glossary/rag — rewritten for definition-intent. Same content, sharper structure: explicit "RAG vs fine-tuning", "RAG vs long context", "RAG vs plain search" sections. Skimmable.
• NEW: How RAG works, and when to use it — the explainer version. Each pipeline step in detail (chunking, embedding, retrieval, hybrid search, reranking, generation), when to use RAG, when not to, 10 common beginner mistakes, and a minimal modern stack.

Glossary = definition. Guide = teaching. Different jobs, cross-linked.

/learn is now structured as a beginner-first hub with three curated paths (New to AI / Use AI at work / Build with AI). Four new cornerstone guides land today:

• Getting started with AI: a 30-minute starter path — the hub guide that links to every other beginner read.
• What AI is good at, and what it still gets wrong — the capability map for new users.
• How to verify AI output before you trust it — opens the new "Verify and trust" pillar.
• Prompts vs Skills vs Workflows vs Agents — when to use which — the decision framework for picking the right AI format for the job.

Also retitled pick-your-daily-ai to "Which AI should I use? Claude vs ChatGPT vs Gemini" to better match how people actually search.

New guide at /learn/ai/use-cases-by-role/best-ai-prompts-for-sales-reps: eight sales prompts that survive contact with real buyers — cold email, discovery openers, objection handling, follow-up sequences, account research, win-back, internal champion enablement, LinkedIn DMs. Each one with the ban-list that keeps the output from sounding generic. Companion piece to the sales prompt library and the Sales pack.

Workflows section is live — 164 templates across 5 packs, 40 free.

• Packs — dev, founder, HR, marketing, sales
• Bundles — per-pack or all-access
• What you get — Claude Code commands, agent runbooks, step-by-step playbooks scoped to a role

New post at /blog/how-to-review-an-ai-pr: a 12-point review checklist for AI-generated PRs — description-vs-diff alignment, import resolution, error handlers, async boundaries, schema drift, injection holes, config permissiveness, and rollback plans — plus how to scope the review so it gets done. Companion piece to AI tests aren't testing anything.

New hub at /mcp: a curated catalog of 31 Model Context Protocol servers across 7 categories — file & code, database, browser & web, productivity, data & analysis, dev-ops, and utility.

• What it is — the 60-second explanation of MCP for people who haven't read the spec, plus a quick rundown of which AI clients support it today (Claude Desktop, Claude Code, Cursor, Zed, Windsurf, Cline).
• 31 hand-picked servers including Anthropic reference (filesystem, git, memory, fetch, time, sequential-thinking), commercial (GitHub, Linear, Notion, Stripe, Sentry, Cloudflare, Vercel, Supabase, MongoDB), and infrastructure (AWS, Docker, Playwright, Firecrawl, Tavily).
• Install snippets — copy-paste claude_desktop_config.json config for the seven reference servers; repo + docs links for the rest.
• Integrated into /search as a new section, and cross-linked from /agents and /glossary/mcp.

Catalog expanded from 179 to 197 tools, with three new categories that were missing for the 2026 landscape:

• Local & on-device AI (6 tools) — Ollama, LM Studio, llama.cpp, Jan, MLX, GPT4All. For running open-weight models without sending tokens to a cloud.
• Evals & observability (6 tools) — Braintrust, Helicone, Langfuse, Arize Phoenix, Patronus AI, LangSmith. The "did my LLM change actually help?" category.
• Sandboxes & code execution (4 tools) — E2B, Vercel Sandbox, Modal, Daytona. Isolated environments for running AI-generated code safely.

Plus two filling existing-category gaps: Vercel (deployment platform — ironically absent until now) and Zed (AI-native code editor).

Seven new prompts in /prompts/code, all targeting AI-builder workflows where verification is the bottleneck:

• Design a verification gate for an AI agent step — treat agent output as hypothesis, define what's checked before it's trusted downstream.
• Review AI-generated output as a hypothesis — sort verified vs assumed vs possibly fabricated, ranked checks to run before accepting.
• Audit a spec for hidden assumptions — find the gaps before an agent or junior engineer fills them with guesses.
• Scope a new build phase with testable acceptance criteria — phase-gated, with explicit exit conditions.
• Generate a debugging hypothesis tree — ranked by likelihood × cheapness-to-verify, not by what's most interesting.
• Design a Postgres data model for a feature — schema, constraints, indexes, denormalization decisions with reasons.
• Write a technical decision record (ADR) — for future-you, six months from now, having forgotten everything.

The /code prompt count is now 20 (was 13).

New post at /blog/pre-deploy-checklist: a 24-point checklist across eight categories (secrets & auth, database, AI costs, frontend, error handling, rate limits, observability, rollback) for AI builders who get 90% of the right decisions and 10% of the catastrophically wrong ones. Includes a copy-paste version.

Major discoverability pass so AINews shows up in Google AI Overviews, ChatGPT citations, and Perplexity:

• New /llms.txt — structured site index for AI crawlers (700+ lines covering every hub, blog post, comparison, glossary term, tool, skill, prompt category, role page, guide, and recent news article). Generated from the same data sources as /sitemap.xml.
• JSON-LD structured data — Organization + WebSite + SearchAction schemas on the homepage; BlogPosting + BreadcrumbList on every blog post. Sitelinks searchbox now eligible.
• Per-post OG images — every blog post now gets a unique 1200×630 image with its title as hero, auto-generated at /blog/[slug]/opengraph-image. Used in social sharing, Twitter cards, LinkedIn unfurl, Slack previews, and BlogPosting JSON-LD.
• Default openGraph.images on layout so every page has a fallback social preview.

Post-promotion sends now lead with the post as hero (with its per-post OG image), not buried under changelog cards. Changes:

• Hero image on top is post-specific (no longer the generic site OG)
• Subject line is the post title (no "AINews · X updates" prefix when promoting a post)
• Larger H1 (30px, weight 800) and CTA button (14×26 padding, 15px font) — matches the site's hero proportions
• Changelog moved to a compact "Also this week" list at the bottom
• Dropped meaningless FEATURE/CONTENT tag pills that appeared on every card
• Digest-only mode (no post) keeps the existing card layout

New post at /blog/vibecoding-what-to-think-about: the five things that actually break when non-engineers ship AI-built apps — API keys in the frontend, fake auth, prompt-deletable databases, uncapped costs, and the "works for me" trap — with a fix for each.

Four changes shipped together:

• New section at /open — opinionated explainer of open-source AI. What "open weights" actually means, the models that matter in May 2026 (DeepSeek V4, Llama 4, Qwen 3.5/3.6, Kimi K2.6, gpt-oss), where to run them, and the open tools built on top. Decision matrix for open vs frontier plus the licensing pitfalls people miss.

• OpenClaw added to the tools catalog — Peter Steinberger's autonomous local AI agent, the fastest-growing open-source project on GitHub. MIT-licensed; runs locally; acts via WhatsApp / Telegram / Discord / Signal with persistent memory.

• "Blog" renamed to "Posts" in nav, footer, and section headers. The content type stays identical (weekly long-form notes); the label was journal-flavored, the actual posts are practical playbooks. URL /blog/[slug] unchanged.

• 17 new sources in /news — Anthropic, Anthropic Engineering, Claude Code Changelog, Google AI, Meta AI, xAI, Mistral, Cohere, Thinking Machines, The Batch, Perplexity, Together AI, Groq, Ollama, Vercel, Windsurf, Simon Willison. Up from 20 to 37 feeds total.

Companion to yesterday's post on hallucinations, loops, and confident-wrongness. New skills you can install:

• AI Output Verifier — audits AI-generated code for hallucinated APIs and silent rewrites
• Loop Breaker — diagnoses why an agent is stuck and produces a clean restart prompt
• Context Grounding Brief — builds the context bundle that prevents hallucinations before they happen
• AI Feature Pre-Ship Checklist — verification checklist for AI-built features before they touch real users

New prompts in /prompts/code (verify AI code, escape an agent loop, ground context before coding), /prompts/productivity (set a time budget for AI tasks), and /prompts/analysis (sanity-check AI output before acting on it).

New post at /blog/your-ai-is-confidently-wrong: the four failure modes that actually empty your AI budget — hallucinations, loops, over-broad rewrites, and long-session degradation — with concrete fixes for each.

Major expansion of /coding:

• Mode picker — pick "Just starting / Solo / Production / Team lead" and get the rest of the page through that lens.
• Recommended starter stacks for each mode (concrete picks, not vague advice).
• Repo file templates — copy-paste AGENTS.md, CLAUDE.md, .cursorrules, PLAN.md, IMPLEMENTATION.md, REVIEW.md.
• Verification matrix — when each level (automated / model review / independent verifier / human) is required.
• Escalation rules for risky changes (auth, payments, destructive migrations).
• Good-vs-bad examples for repo instruction files.

Plus 9 new AI builders in /tools: Codeium, Cody by Sourcegraph, Emergent, Base44 (Wix), Natively, Supermaven, StackBlitz, JetBrains AI Assistant, Amazon Q Developer.

Full pre-launch security audit and patch round. Closed:

• Stored XSS vector in JSON-LD (escaped </script> and U+2028/2029 properly).
• DB credential footgun in Next config.
• Missing rate limits on LLM endpoints (per-IP + body fingerprint).
• Newsletter mailbomb risk (rate limit + honeypot + per-recipient cooldown).
• Missing security headers (CSP, HSTS, frame, referrer, nosniff, permissions).
• Removed two obsolete privileged setup routes.

Site is now safe to deploy publicly.

First public version of AINews. Hand-curated AI reference site for builders:

• 128 Claude Skills across 12 packs (developer, founder, marketer, sales, HR, customer success + capability packs for slides, sheets, docs, PDFs, web/UI, diagrams).
• 100 prompts organized by job-to-be-done.
• 178 AI tools with comparisons.
• /learn guides on validation, distribution, pricing, integration, automation.
• /glossary of 80+ AI terms in plain language.
• /for/[role] role-specific stack recommendations.

All free, no signup, MIT-licensed code, CC BY-NC content.